HLA-B*57 micropolymorphism shapes HLA allele-specific epitope. immunogenicity, selection pressure and HIV immune control

Transcription

1 JVI Accepts, published online ahead of print on 16 November 2011 J. Virol. doi: /jvi Copyright 2011, American Society for Microbiology and/or the Listed Authors/Institutions. All Rights Reserved HLA-B*57 micropolymorphism shapes HLA allele-specific epitope immunogenicity, selection pressure and HIV immune control Henrik N. Kloverpris 1*, Anette Stryhn 2, Mikkel Harndahl 2, Mary van der Stok 3, Rebecca P. Payne 1, Philippa C. Matthews 1, Fabian Chen 5, Lynn Riddell 6, Bruce D. Walker 3,4, Thumbi Ndung u 3, Søren Buus 2 and Philip Goulder 1,3,4 1 Department of Paediatrics, University of Oxford, Peter Medawar Building, OX1 3SY, United Kingdon, 2 Department of International Health, Immunology and Microbiology, University of Copenhagen, 2200-Copenhagen N, Denmark, 3 HIV Pathogenesis Program, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban, 4013, South Africa, 4 Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard, Boston, MA Department of Sexual Health, Royal Berkshire Hospital, Reading RG1 5AN, United Kingdom, 6 Department of Genitourinary Medicine, Northhamptonshire Healthcare National Health Service Trust, Northhampton General Hospital, Cliftonville, Northhampton NN1 5BD, United Kingdom. *Corresponding author. Running title: Distinct targeting of HLA-B*5702, HLA-B*5703 and HLA-B*5801 restricted epitopes Key-words: HIV-1, Micropolymorphism, HLA-B*5702, B*5703, B*5801, Immune control, CD8+ T cell, HLA-class I peptide binding, stabililty and tetramers Character count: 32,824 (excluding Materials and Methods, References, Tables, and Supplemental material) 1

2 ABSTRACT The genetic polymorphism that has the greatest impact on immune control of human immunodeficiency virus (HIV) infection is expression of HLA-B*57. Understanding the mechanism for this strong effect remains incomplete. HLA-B*57 alleles and the closely-related HLA-B*5801 are often grouped together because of their similar peptide-binding motifs and HIV disease outcome associations. However, we show here that the apparently small differences between HLA-B*57 alleles, termed HLA-B*57 micropolymorphisms, have a significant impact on immune control of HIV. In a study cohort of >2000 HIV C-clade infected subjects from Southern Africa, HLA-B*5703 is associated with lower viral set-point than HLA-B*5702 and HLA-B*5801 (median 5980, and HIV copies/ml plasma, p=0.24 and p=0.0005, respectively). In order to better understand these observed differences in HLA-B*57/5801- mediated immune control of HIV, we undertook, in a study of >1000 C clade infected subjects, a comprehensive analysis of the epitopes presented by these 3 alleles and of the selection pressure imposed on HIV by each response. In contrast to previous studies, we show that each of these three HLA alleles is characterised both by unique CD8+ T-cell specificities and by clear-cut differences in selection pressure imposed on the virus by those responses. These studies comprehensively define for the first time the CD8+ T-cell responses and immune selection pressure for which these protective alleles are responsible. These findings are consistent with HLA class I alleles mediating effective immune control of HIV through the number of p24-gagspecific CD8+ T-cell responses generated that can drive significant selection pressure on the virus. 2

3 INTRODUCTION HLA-B*57 is the HLA allele which has the greatest impact on viral load set-point, and rate of disease progression in HIV (10, 17, 18, 23, 28, 29, 34, 42, 47, 56). However, critically for development of a vaccine designed to optimise immune control of HIV infection, the mechanism by which HLA-B*57 is linked to relatively successful control of HIV infection remains incompletely understood. In studies of a large Southern African cohort in Durban, the number of Gag-specific CD8+ T cell responses induced, and the number of Gag escape mutants selected correlated with viral load set-point (30, 40), with HLA-B*5703 being associated with the lowest viral set-point, the highest number of Gag epitopes targeted, and the highest number of Gag escape mutations selected. In addition, HLA-mediated immune control of HIV has been linked to natural killer cell activity, with Bw4-80I alleles such as HLA-B*57 being ligands for the inhibitory KIR3DL1 receptor (37) and also for the activating KIR3DS1 NK cell receptor (9, 37, 45). The subtype of HLA-B*57 most prevalent in Sub-Saharan Africa, the region worst-affected by the global HIV epidemic, is HLA-B*5703, which is the allele associated with the lowest viral loads in this region (11, 27, 29, 31, 34, 41, 55). HLA-B*5703 differs by only a single amino acid from the other HLA-B*57 subtype arising at significant levels in these populations, HLA- B*5702 (Leu at HLA residue 156 in HLA-B*5703 and Arg at residue 156 in HLA-B*5702). HLA-B*5801 differs in the alpha 1 and 2 domains by 7 amino acids from HLA-B*5703, and by 6 residues from HLA-B*5702. However, the published peptide-binding motif for all three closelyrelated HLA alleles is identical (5, 15): Thr/Ser/Ala at position 2 in the peptide, binding in the B- pocket of the HLA molecule, and Trp/Phe/Tyr at the carboxy-terminal position in the peptide, 3

4 binding in the F-pocket of the HLA molecule. Because of these similarities, and in order to increase statistical power, the closely-related HLA-B*5702, HLA-B*5703 and HLA-B*5801 alleles have often been analysed together in studies of HIV infection (19, 23, 35, 38)). This has appeared justified, since some of the same CD8+ T-cell epitopes are presented by these three alleles, and in some cases these responses appear, superficially, to impose the same selection pressure on the virus. An example is the Gag epitope, TSTLQEQIAW ( TW10, Gag ), presented by all 3 closely related alleles; and, within TW10, in each case, the same escape mutant T242N is commonly selected. However, closer inspection of this TW10 response, and the other HIV-specific epitopes presented by these related alleles, without exception, reveals differences that may be relevant to understanding why HLA-B*5703 is linked to superior immune control of HIV. In these studies we focus on the differences between HLA-B*5702, HLA-B*5703 and HLA- B*5801 associated with improved immune control of HIV in C-clade infection, KwaZulu-Natal, South Africa. Although these three alleles are all significantly associated with lower viral load set-point than study subjects not expressing these alleles, HLA-B*5703 is associated with a significantly lower viral set-point than HLA-B*5801 (p=0.0005, Mann Whitney test), and B*5801 is associated with a significantly higher absolute CD4 count than either B*5702 or B*5703 (p=0.0019, p=0.0025, data not shown). To determine whether differences in the viral setpoint associated with these three closely-related HLA class I alleles could be related to epitope specificity, or to the ability of certain responses to exert selection pressure on the virus, as has been previously hypothesised (40), we undertook for the first time a comprehensive analysis of the CD8+ T-cell responses restricted by this group of alleles in a study of >1,000 adults with 4

5 chronic C-clade infection. In addition, we identified the epitope-specific CTL responses that are capable of exerting selection pressure on the virus. These data were then related to differences in viral setpoint linked to these protective HLA alleles

6 MATERIALS AND METHODS Study subjects We studied a total of 2,093 adults with chronic, antiretroviral therapy (ART)-naïve HIV-1 infection, recruited from four cohorts as follows: (i) Durban, South Africa (C-clade, n=1263), as previously described (13, 16, 29, 40); (ii) Gaborone, Botswana (C-clade, n=525) via the Mma Bana study, (iii) Bloemfontein, Free State, South Africa (C-clade, n=261), as previously described (27) and (iv) Kimberley, South Africa (n=44). Data describing viral loads and CD4 T cell counts were available in 1,869 and 1,849 subjects, respectively in all of whom HLA typing to four-digit resolution had been determined. CD4+ T cell counts were determined for 23 HLA- B*5702, 73 HLA-B*5703 and 198 HLA-B*5801-positive individuals, respectively, and for 1555 subjects expressing none of these 3 alleles. Viral load was measured using the Roche Amplicor version 1.5 assay. Informed consent was obtained from all participating individuals and institutional review boards at the University of KwaZulu-Natal, Massachusetts General Hospital and University of Oxford approved the study. Elispot and optimal peptide mapping In 1,010 HIV C-clade infected subjects the HIV-specific CD8+ T-cell responses were determined in IFNγ elispot assays. Responses were determined to a set of 410 overlapping peptides (OLPs), whose sequence was based on the 2001 C-clade consensus arranged in a matrix system with peptides in each pool. Responses to matrix pools were deconvoluted by subsequent testing with the individual 18mer peptides within each pool, and the identity of the individual 18mers recognized were thus confirmed, as previously described (29). For epitope mapping of the optimal peptide and recognition of response to mutated escape peptides, we titrated the individual 6

7 peptides over a range of 8 logs using 100,000 input cells in each well as described previously (46) HLA class I typing Four digit high resolution typing of HLA-A, HLA-B and HLA-C alleles were performed using the Dynal RELTIM reverse sequence-specific oligonucleotide (SSO) kits as previously described (26). HLA restriction assay and presentation of peptide on HLA To determine which HLA allele presenting the peptide of interest, we generated a panel of EBVtransformed B lymphoblastoid cell lines (BCL) each matching the effector cells through one HLA allele as previously described (22). Briefly, BCL cells were incubated with 50 μg/ml of peptide or no peptide for 1 hour and washed thoroughly 4 times. We generated effector cells by stimulating PBMCs with peptide (50 μg/ml) for 7-10 days and for further rounds of stimulation we used irradiated peptide pulsed HLA-matched BCL and feeder cells in effector:bcl:feeder ratio of 1:1:1. Effector cells were grown for 2-4 weeks prior to use in assay in order to obtain a higher frequency of peptide-specific CD8+ T cells as previously described (46). For HLA restriction, CTLs were co-cultured with BCL in a 1:2 ratio for 6 hours at 37ºC, 5% CO 2 in the presence of Brefeldin A (10μg/ml) and anti CD107a (1:25) and subsequently stained in an intracellular cytokine staining assay using the following surface antibodies CD8 AlexaFlour 750 (ebioscience), CD3 AlexaFlour 700 (BD) and live/dead violet cell stain kit (Invitrogen), fixed and permeabilized (BD cytofix/cytoperm kit) and stained intracellular with IFNγ PE-Cy7 (BD) and MIP1β FITC (R&D) and fixed in 2% paraformaldehyde. Samples were acquired on a LSR II 7

8 (BD) flowcytometer within 12 hours of staining and analysed using FlowJo version Cells were hierarchically gated on singlets, lymphocytes, live cells, CD3+ T cells, CD8+ T cells and analyzed for IFNγ+MIPβ+ or CD107a+MIP1β+ double positive events Tetramer synthesis and tetramer staining. Tetramers were generated as previously described (32). For staining of PE or APC-conjugated tetramer specific cells, PBMCs were thawed into R20 media, rested for one hour at 37ºC, 5% CO 2, and stained with HLA-class I tetramer for 30 mins at room temperature, washed and surface stained with CD8 AlexaFlour 750 (ebioscience), CD3 AlexaFlour 700 (BD) and live/dead violet cell stain kit (Invitrogen) for 30 mins, washed in PBS and fixed in 2% paraformaldehyde. Samples were acquired on a LSR II (BD) flowcytometer within 12 hours of staining and analysed using FlowJo version Cells were hierarchically gated on singlets, lymphocytes, live cells, CD3+ T cells and double gated for a distinct tetramer specific CD8 positive population. Sequencing of proviral DNA Sequences from Gag, Pol and Nef were generated by extraction of genomic DNA from peripheral mononuclear cells (PBMCs) and amplified by nested PCR using previously published primers (26) and the PCR product purified as previously described (40). Sequencing was undertaken using the Big Dye ready reaction mix as described (16, 33) and in this way HIV Gag, Pol and Nef sequences were obtained from 1209, 446 and 436 study subjects, respectively (40) and Vif, Rev and Env sequences were obtained from HIV full-length sequencing available for 248 study subjects as previously described (49). 8

9 HLA-peptide binding and stability assays The measurement of peptide MHC-I stability was determined as recently described (25) and peptide MHC-I affinity interactions were undertaken using the AlphaScreen technology as previously described (24) Statistical method to identify HLA and OLP associations We used a decision tree based on Fisher s exact test to identify associations between the recognition of individual 18-mer peptides and the expression of HLA-B*5702, HLA-B*5703 and HLA-B*5801. For each 18-mer peptide, we computed the Fisher exact test p-value against all 4- digit HLA alleles observed in the cohort and added the most significant HLA allele to the decision tree. We next removed all individuals who expressed that allele and repeated until the most significant HLA allele had p>0.2. False discovery rates (6) were calculated using a procedure specific to Fisher s exact test that analytically computes the null distribution for all permutations of the data, as previously described (8). For comparison of viral load and CD4 T cell counts we used the Mann-Whitney U test as previously described (30). We used Mann- Whitney U test to compare immunogenic epitopes against non-immunogenic for HLA-peptide binding affinities and HLA-peptide stabilities, and the Spearman Rank model to test the correlation between percentage of individuals responding (IFNγ elispot) to a particular peptide and to the peptide binding values (IC50 Kd [nm]) and peptide HLA stability [hrs] for a particular HLA. 9

10 RESULTS HLA-B*5703 is associated with lower viral set-point and higher CD4+ T-cell count than HLA-B*5801 We focused on three HLA alleles associated with control of HIV, HLA-B*5702, HLA-B*5703, and HLA-B*5801 expressed in 1.4%, 4.4%, and 11.9%, respectively, in a large cohort (n=2,093) of well-characterized chronic HIV C-clade infected individuals. These closely-related alleles, HLA-B*5702, HLA-B*5703 and HLA-B*5801, are all associated with significantly lower viral load set-point than study subjects not expressing these alleles (median setpoint 15190, 5980, 19000, and HIV RNA copies/ml plasma, respectively, Fig 1). HLA-B*5703 is associated with a significantly lower viral set-point than HLA-B*5801 (p=0.0005) and lower viral set-point than HLA-B*5702, although this latter difference was not statistically significant (p=0.2). In this cohort of chronically infected subjects, absolute CD4 T cell counts were also significantly higher in individuals expressing any of HLA-B*5702, HLA-B*5703 or HLA-B*5801, compared to those not expressing them (706/mm 3, 516/mm 3 and 412/mm 3 versus 336/mm 3, respectively, p< in each case, data not shown). Distinct p24 Gag epitope targeting and differential selection pressure imposed The differences in amino acid residues between HLA- B*5702, B*5703 and B*5801 are shown in Table 1. To investigate the consequence of these difference with respect to epitopes targeted, we initially focused on the four well-characterised p24 Gag epitopes restricted by HLA- B*57/5801, since these responses have been most frequently implicated in studies addressing the association between HLA-B*57 and slow HIV disease progression (40). These are: ISPRTLNAW ( ISW9, Gag ), KAFSPEVIPMF ( KF11, Gag ) TSTLQEQIAW 10

11 ( TW10 Gag ) and QATQDVKNW ( QW9, Gag ). Three of these p24 Gag epitopes are listed in the Los Alamos Immunology database A list as restricted by HLA- B*5701, namely, ISW9, KF11 and TW10. KF11 is listed also as restricted by HLA-B*5703, and TW10 is listed as also restricted by HLA-B*5801. QATQDVKNW ( QW9, Gag ) is only listed as HLA-B*5801 restricted. Testing recognition of these optimal epitopes in elispot assays showed clear differences in recognition according to the HLA type expressed (Fig 2A). The dominant HLA-B*5703-restricted KF11 epitope was targeted by 76% of subjects expressing HLA-B*5703, compared to 0% and 10% of subjects expressing HLA-B*5702 and B*5801, respectively (p=0.01 and p=3x10-7, respectively, Fisher s Exact Test). ISW9 is targeted significantly less often by subjects expressing HLA-B*5801 than those expressing HLA-B*5702 or B*5703 (p=0.01 and p=2x10-6, respectively), whereas TW10 is preferentially targeted by HLA-B*5801-positive subjects compared to B*5703 and B*5702 (Fig 2A). These differences in epitope recognition are, in some cases, at least partially explained by corresponding differences in the selection of escape mutants. Thus, higher recognition of TW10 in subjects with HLA-B*5801 is reflected by lower frequencies of escape mutants at T242 and I247 (Fig 3). However, it is clear that for ISW9 and KF11, these are epitopes that are not recognized at significant levels by subjects with HLA-B*5801, and not is there escape mutation selected within these epitopes in these subjects; similarly, KF11 is neither recognised in HLA- B*5702-positive subjects, nor are escape mutants selected within KF11 in these subjects. With respect to QW9, targeted by a minority of subjects expressing HLA-B*5702 or HLA-B*5703 or HLA-B*5801, only was significant selection for the T310S escape mutant within QW9 (at P3 in the epitope, Fig 3DE) observed in subjects expressing HLA-B*5801. However, this selection 11

12 pressure was relatively weak, mutants observed only in 10-15% of HLA-B*5801-positive subjects Thus, there are clear-cut differences between these three closely-related HLA alleles with respect to these four p24 Gag-specific epitopes. From the elispot assays and sequence data shown, HLA- B*5703 restricts three p24 Gag-specific CTL responses that impose strong selection pressure on the virus (ISW9, KF11 and TW10-specific responses), whereas HLA-B*5702 and HLA-B*5801 restrict two (ISW9/TW10 and TW10/QW9, respectively). Including the non-b*57/5801 HLA-B alleles in this analysis, which collectively restrict on average 0.32 (7/22) p24 Gag epitopes per allele within which escape mutants are selected (40), these data provide a correlation between viral load set-point and number of p24 Gag epitopes at which escape mutants are selected (r 2 =0.99, p=0.007) (Fig 3F). All HIV-specific responses restricted by HLA-B*5702/5703/5801 alleles exhibit distinct patterns of targeting and selection pressure To determine whether the findings described in relation to the four well-characterised CD8+ T cell epitopes restricted by HLA-B*5702, B*5703 and HLA-B*5801 apply more generally to the other HIV-specific epitopes restricted by these three closely-related alleles, we first employed a panel of mer peptides overlapping by 10 amino acids spanning the C clade proteome as previously described (30), to provide as comprehensive a description as possible of all the epitopes restricted by these closely-related alleles HLA-B*5702, HLA-B*5703 and HLA- B*5801. The study cohort of 1,010 adults with chronic C clade infection studied for responses to these 410 peptides in IFNγ elispot assays included 14 HLA-B*5702-positive/HLA- 12

13 B*5703/B*5801-negative subjects, 56 HLA-B5703-positive/HLA-B*5702/B*5801-negative subjects, 100 HLA-B*5801-positive/HLA-B*5702/B*5703-negative subjects and 837 subjects expressing none of these alleles. One subject coexpressed HLA-B*5703 and HLA-B*5801 and was therefore excluded from analysis. From this evaluation, apart from the 4 p24 Gag responses described above, we identified additional 4, 11 and 9 epitopes that are presented by HLA- B*5702, HLA-B*5703, and HLA-B*5801, respectively (Fig 2B, Suppl. Fig 1 and Table 2). Thus there are in total 17 epitopes presented by one or more of these HLA molecules, of which only 5 are listed as optimal epitopes in the Los Alamos Immunology database A list for any of these 3 alleles (Table 2). Despite the apparently identical peptide binding motifs described (5, 15) for HLA-B*5702, HLA-B*5703 and HLA-B*5801, distinct patterns of epitope targeting were observed for all these epitopes (Fig 2B and Supplementary Fig 1). The epitopes within OLP-5- p17, 263/4-Int and 411/2-Vif were uniquely presented by HLA-B*5703 and 95/6-Rev by HLA- B*5801. The epitopes within OLP-216-RT, 257-Int, 77/8-Nef, 82-Nef and 296-Env were restricted by both B*5703 and B*5801 alleles. HLA-B*5702 presents only a minority of welltargeted epitopes (FF9 RT and QF10 RT). In order to demonstrate the validity of this approach in identifying novel epitopes restricted by these alleles, we proceeded in selected cases to define the optimal epitope and HLA restriction. We first selected the novel overlapping peptide (OLP)-411/12 Vif response, since targeting this 18mer OLP previously had been shown to be associated with significantly high viral loads in HLA-B*5703-positive individuals (30). This association is strengthened in the bigger cohort studied here (median viral setpoint in Vif LW9 responders: 26,492 vs. 1,705 in Vif LW9 nonresponders, HIV RNA copies/ml plasma, p=0.005, data not shown). Peptide truncations 13

14 demonstrated the optimal epitope to be the 9-mer LGHGVSIEW, ( LW9, Vif 81-89) (Fig 4A) and a panel of BCLs were used to confirm the restriction element as HLA-B*5703 (Fig 4B). The identity of this optimal epitope was further confirmed when we demonstrated staining of the relevant antigen-specific cells using an HLA-B*5703-LW9 tetramer (Fig 4C) We then proceeded to adopt this tetramer-based approach to demonstrate the optimal epitopes and HLA restriction for an additional selection of the 13 novel epitopes identified by the elispot assays (Fig 5). Whilst only two of these epitopes (KF9 Int and HW9 Nef) have previously appeared in the Los Alamos Immunology Database as HLA-B*5701-restricted, the restriction of these two epitopes by HLA-B*5702, HLA-B*5703 or HLA-B*5801 has not been demonstrated before. In addition, 7 of the epitopes described here (DW10 p24, FF9 RT, QF10 RT, QY10 Rev, LW9 Vif, TW9 Env and KW9 Env) are entirely novel whereas 2 epitopes have only previously been shown to be presented by HLA-B*57 (IW9 RT and SW10 Int) (23, 48) and KF9 Nef only described for HLA-B*5801 (33). Since the efficacy of a CD8+ T-cell response has been related to its ability to drive selection pressure on HIV, we next sought to characterise the selection of escape mutants within epitopes from the entire HIV proteome for individuals expressing either HLA-B*5702, B*5703, B*5801 and subjects not expressing any of these three alleles (Fig 6). Among these data, it is also clear that, as with the p24 Gag epitopes, the identical epitope-specific response can have substantially different impact depending on the particular presenting HLA allele as identified for 6 additional epitopes here. Of note, no significant selection of escape was observed for the 4 Env/Rev/Vif epitopes. 14

15 Peptide binding affinities to HLA-B*5702, HLA-B*5703 and HLA-B*5801 and peptide:hla stability partially explain distinct epitope targeting In order to address possible mechanisms by which distinct epitope targeting is observed, and differential selection pressure is imposed on HIV by these three closely related HLA alleles, despite the binding motifs for HLA-B*5702, B*5703 and B*5801 being reportedly identical (5, 15), we tested the hypothesis that different epitope binding affinities and peptide:hla stabilities might contribute. Of 15 peptides that were available for testing, differential targeting of 5 epitopes were explained by either peptide binding affinities, HLA:peptide stabilities or both (Fig 7). For example, HLA-B*5801 is the only allele not associated with ISW9p24 targeting or escape and this allele has almost 10 times lower binding affinity for ISW9 than does HLA-B*5703 and B*5702 (Kd= 155nM, 11nM and 19nM, respectively) and 5 times lower peptide-mhc stability (t1/2 being 1.1hrs, 5.2hrs and 5.7hrs, respectively). However, for the remainder of epitopes tested, HLA-peptide binding affinity or HLA-peptide stability differences did not explain the observed HLA differences. Thus, the distinct targeting of epitopes and selection of escape mutations by HLA-B*5702, B*5703 and B*5801 expressing individuals could, for approximately only one-third of these epitopes, be explained by differential binding affinities and peptide:hla stabilities. Since recent studies have indicated that peptide-mhc I stability may be a better predictor of immunogenicity than peptide MHC I binding affinity (43), we compared the contribution of these two measures to peptide immunogenicity for the optimal epitopes shown above in the 170 individuals studied expressing HLA-B*5702, B*5703 or B*5801 (n=14, n=56 and n=100, 15

16 respectively) (Fig 8). Although there was a statistically significant difference between immunogenic and non-immunogenic peptides (Table 2) in peptide:hla binding affinities (Fig 8A) and peptide:hla stabilities (Fig 8B) (p=0.04 and p=0.0008, respectively, Mann Whitney U test), peptide-hla binding stability did not predict peptide recognition any better than peptide- HLA affinity (Fig 8C-D, Suppl Fig 3). Furthermore, these data highlight that factors other than peptide-mhc binding affinity and stability also play an important role in determining immunogenicity. Notable absence of previously listed HLA-B*57/5801-restricted epitopes The approach we used here to define the epitopes restricted by HLA-B*57/5801 molecules, in addition to identifying as comprehensively and in as unbiased a fashion as possible also highlighted some notable absences of previously reported epitopes. For those we tested the ability of the peptides to bind and in some cases these proved not to bind. For example, HLA-B*5701- restricted epitopes published include KAIGTVLV (KV8 Pro), YTPGPGIRY (YY9 Nef), YFPDWQNYT (YT9 Nef) (14, 20, 21, 52), none of which fit the peptide binding motif for HLA- B*5701 and none bind HLA-B*5701 (Kd nm >20,000, data not shown). These data highlight the value of the approach adopted here to define the epitopes restricted by different HLA alleles, and the unequivocal confirmation of optimal epitopes and HLA restriction provided by use of tetramers as shown here. Taken together, this comprehensive characterisation of IFNγ OLP responses and sequence polymorphisms in a large C-clade cohort with the use of MHC class I tetramers, peptide binding and peptide HLA stability assays reveals distinct targeting of CD8+ T cell epitopes within HLA- 16

17 B*5702, B*5703 and B*5801 restriction (Table 2). Importantly, HLA-B*5703 selects escape mutations in 3 of the well characterised p24 capsid epitopes ISW9, KF11 and TW10, whereas HLA-B*5702 and B*5801 only selects escape in 2 of these epitopes, respectively, which may explain the improved immune control of HIV as observed in HLA-B*5703 over HLA-B*5702 and HLA-B*5801-positive individuals. 356 Downloaded from on June 30, 2018 by guest 17

18 DISCUSSION Recent analyses of the STEP trial suggest that T-cell vaccination strategies can be successful, but only if effective CD8+ T-cell responses are induced, and in this case these were only seen in subjects expressing the already protective alleles HLA-B*27/57/5801 (1, 19). This highlights the importance of fully understanding which specific responses mediate improved immune control of HIV, to guide future HIV vaccine design. The study presented here is the first to comprehensively define what epitopes are targeted by HLA class I alleles most strongly associated with outcome of immune control in adult chronic C-clade HIV infection. Despite HLA-B*57/5801 alleles having been well studied, it has remained unclear which epitopes are presented and to what extent they are targeted. Here we report a detailed characterisation of all the epitopes within the HIV proteome that are restricted by any of three closely-related, protective HLA alleles, HLA-B*5702, B*5703 and B*5801, that are significantly targeted in a large cohort (n>1000) of chronically infected study subjects. Having undertaken this analysis we conclude that HLA restriction has a distinct impact on both the immunogenicity and the selection pressure imposed on the virus by each response. In addition, the differences in control of disease progression observed for these closely-related HLA alleles are most clearly correlated with the number of p24 Gag-specific responses that drive significant selection pressure on the virus. The amino acid differences between the 3 closely-related HLA-B*57/5801 alleles represent micropolymorphisms, a termed previously coined in relation to three closely-related HLA-B*44 alleles, HLA-B*4402, HLA-B*4403 and HLA-B*4405, that differ at two positions, 116 and 156 (Table 1) (2). This HLA-B*44 study showed that the amino acid changes do not alter the TcR contact sites on the MHC, but alter the confirmation observed for peptide residues 4-7 for the 18

19 three HLA-B*44 alleles. The same principle may apply for peptides presented by HLA-B*5702, B*5703 and B*5801 where they bind the same peptides but may present these peptides in a very different peptide:mhc landscape. For example, HLA-B*4402 and HLA-B*4403 differ only by one amino acid, and in the same position (Asp and Leu at residue 156, respectively) as HLA- B*5702 and HLA-B*5703 (Arg and Leu at residue 156, respectively). Crystal structures of the same peptide presented by HLA-B*4402 and B*4403 showed a wider peptide-binding cleft for HLA-B*4403, compared to HLA-B*4402, and, whilst the majority of peptides presented by HLA-B*4403 are also presented by HLA-B*4402, a broader repertoire of unique peptides are presented by HLA-B*4403 (36). The hydrophobic side chain in residue 156 for HLA-B*5703 (156-Leu) may similarly disrupt water-mediated hydrogen bonds serving to keep the peptidebinding cleft relatively narrow in HLA-B*5702 (156-Arg) compared to HLA-B*5703. This may alter the precise orientation of the same peptide in the groove of B*5702 versus B*5703, as well as increasing the number of possible epitopes presented by HLA-B*5703 compared to HLA- B*5702, as is observed here (Table 2). Other studies of the HLA-B*41 family show how 6 HLA- B*41 subtypes, differing in 6 MHC-I residues, present different peptides of various different length and thereby create structurally distinct peptide-hla complexes (4). These studies underline the consequences of HLA micropolymorphism changes in residues lining the peptidebinding groove. In this study, the impact of only one residue change between HLA-B*5703 and B*5702 on peptide presentation was highly evident as these alleles only share 50% of the HIV epitopes, with an additional 7 more epitopes targeted by HLA-B*5703 than HLA-B*5702. The larger repertoire of unique epitopes presented by HLA-B*5703 is of particular interest in relation to the KF11 Gag 19

20 epitope, targeting of which has been associated with lower VL compared to HLA matched nonresponders (30) and in which the accumulation of escape mutations increasingly cripples the virus, thereby facilitating immune control (12) (13). HLA-B*5703 is the only one of these closely-related HLA-B*57/5801 molecules capable of a broad p24 Gag-specific response. The differential targeting of these well-studied epitopes in p24 Gag, ISW9, KF11, TW10 and QW9, is related to viral setpoint, in that HLA-B*5703 targets all 4, while HLA-B*5702 and B*5801 target three and two, respectively. This result is consistent with our previous findings, (40) which showed that viral setpoint associated with each HLA-B allele is correlated with the number of Gag responses restricted by that respective HLA-B allele (r=-0.49, p=0.013). Our findings here also support an additional result from that study, namely, that the ability of a particular HLA-Brestricted Gag response to impose selection pressure on the virus is more strongly correlated with viral setpoint (in Matthews et al, r=-0.62, p=0.0009). Here, we have shown that the only Gag epitopes restricted by HLA-B*5702/5703/5801 alleles, where there is evidence of escape, are ISW9, KF11, TW10 and QW9. Furthermore, if one compares the number of p24 Gag epitopes restricted by these 3 HLA-B*57/5801 alleles that show evidence of escape (ISW9 and TW10 for B*5702, TW10 and QW9 for B*5801, ISW9, KF11 and TW10 for B*5703) with the number of Gag responses driving escape via the other 22 HLA-B alleles (7 responses divided among 22 alleles, mean 0.32 responses/allele), one arrives at a remarkably strong correlation with viral setpoint (Fig 3F). Although it is clear that many other factors contribute to viral setpoint in addition to the number of CD8+ T-cell Gag responses that can impose selection pressure on the virus, nonetheless it is a surprisingly strong correlation given the small number of datapoints available. Of note, no such correlation of type was observed when we considered epitopes in Pol, in the Accessory/Regulatory proteins, or in Env. However, other mechanisms may also be 20

21 involved, such as the different linkage disequilibrium (LD) to HLA-A and Cw alleles. In particular, the LD of HLA-B*5703 with HLA-A*7401 has recently been shown to have an additive effect for the immune control from HLA-A*7401 (34, 39), whereas HLA-B*5801 in LD with HLA-A*0205, for example, may not add any beneficial effect From the comprehensive sequence analysis of escape mutants within the 17 epitopes studied here (Fig 3 and 6), we note that sequence variability from the wildtype consensus is present in >50% for individuals not expressing HLA-B*5702, B*5703 and B*5801 for 5 of these epitopes (LF11- p17, FF9-Pol, IAW9-Pol, KF9-Nef and HW9-Nef). The accumulation of the A83G mutant within KF9-Nef and H119N within HW9-Nef, selected by HLA-B*57/5801, and M377L within IAW9 selected by HLA-B*5801, may represent epitopes being driven towards extinction (33) precipitating new consensus sequences. In the case of LF11-p17 and FF9-Pol the high sequence variability may not be driven by HLA-B*57/5801 but may result from epitope clustering and selection pressure imposed by other alleles on overlapping epitopes. This finding raises the possibility that protection from HLA-B*5702, HLA-B*5703 and B*5801 may alter over time. However, whether this protection increases or decreases as a result of such changes is unknown. Taken together, these data support the hypothesis that a broad Gag-specific response is protective against HIV disease progression, that Gag-specific responses capable of driving selection pressure on the virus have the strongest protective effect, and that the outstanding difference between HLA-B*5703 and the other closely related HLA alleles, HLA-B*5702 and HLA- B*5801, is the immunodominant response towards KF11. 21

22 As described above, we have illustrated an approach to characterising the significant CD8+ T-cell responses restricted by different HLA class I alleles, which is not biased by use of peptidebinding motifs, and in which confirmation by peptide-mhc tetramer demonstrates both the optimal epitope and the restriction element. There are relatively common examples in the literature of epitopes that prove to have been incorrect in sequence and/or by HLA restriction (14, 20, 21, 52). In this paper we also took advantage of the opportunity to assess the part in immunogenicity played by peptide-mhc binding avidity and peptide-mhc stability half-life and found significant differences between immunogenic and non-immunogenic optimal peptides, which is in agreement with other findings (Harndahl M. et al. unpublished and Kloverpris H. et al unpublished). We also found significant correlations between the percentage of chronicallyinfected subjects recognising the peptide and peptide-mhc binding avidity and peptide-mhc stability. However, the Spearman Rank Correlation (r) values found here were moderate, which is not unexpected, and indicates that other factors also influence immunodominance, as comprehensively reviewed by others (58, 60) (3, 54, 58, 59). Presentation of a MHC-class I restricted epitope to a specific CD8+ T cell is the culmination of a number of individual upstream events, including proteasome cleavage of viral proteins, transported to the ER lumen by transporters associated with antigen (TAP) and further N-terminal trimmed by ERAAP1/2 before peptide loading onto empty MHC class I molecules by the peptide loading complex (PLC), and subsequent trafficking to the cell surface via the Golgi apparatus for recognition of CD8+ T cells (57, 60). In addition to these processing events, the availability of CD8+ T cells expressing T cell receptors (TcRs) specific for the processed peptide applies another level of complexity 22

23 influencing immunodominance as TcR selection from a vast naïve T cell repertoire containing millions of unique TcRs, is not a stochastic process but routinely ordered and biased (44). Furthermore, protein abundance differs substantially, in the case of HIV proteins representing an immunogenicity advantage for the highly abundant Gag epitopes (7, 53); and some protein epitopes are presented earlier in the viral life cycle than epitope from other viral proteins (50, 51). In addition, the presence of viral sequence escape mutations will further affect immunogenicity. Therefore, the measurement of peptide binding and peptide stability to the HLA molecule is unlikely to predict precisely the outcome of this very complex set of individual events important for immunogenicity. However, it is evident that peptide-mhc binding is a necessary but not sufficient requirement for the initiation of a CD8+ T cell response (3, 54, 58, 59). This is exemplified by the low LW9-B*5702 stability half-life (<0.5hrs) (Fig 7D), which results in a complete lack of detectable LW9 specific CD8+ T cell responses in subjects expressing HLA- B*5702 (Fig 7C). In conclusion, this study defines the differences between three closely-related, protective HLA class I alleles, in terms of the epitopes presented that are targeted by a large cohort of HIVinfected study subjects, and in terms of the selection pressure imposed by these responses on the virus. These data support earlier findings (40) that the critical differences distinguishing HLA alleles are the breadth of the Gag-specific CD8+ T-cell response, in particular the p24 Gagspecific response, and the ability of those responses to drive selection pressure on the virus. 23

24 FIGURE LEGENDS Figure 1. Association of HLA-B*57/B*58 allele expression with steady-state viral load in a cohort size of 1,864 C-clade chronically infected individuals from Southern Africa. Y-axis shows the association to viral load (RNA copies/ml) expressed as interquartile ranges with the number of individuals included in the analysis for each parameter and HLA shown on the x-axis. All HLAs were mutually excluded for co-expression of any of the other HLA-B*57/58 alleles. Significant difference between groups is indicated by p-values shown above bar (Mann-Whitney U test). Figure 2. IFNγ elispot responses to 17 HIV CD8+ T cell epitopes. A. Four p24 capsid Gag optimal peptides screened in 9, 25 and 44 HLA-B*5702, HLA-B*5703 and B*5801 individuals, respectively expressed as % recognition of the peptide, ISW9 (ISPRTLNAW), KF11 (KAFSPEVIPMF), TW10 TSTLQEQIAW and QW9 (QATQDVKNW) indicated on the x-axis. B. Associations of IFNγ elispot responses to 18mer peptides in HLA-B*5702, B*5703, B*5801 expressing and HLA-B*57/58 negative individuals expressed as % responders (y-axis) to 13 18mer peptides grouped according to 4 different HLA-B*57/58 expression with the 18mer peptide number and epitope abbreviation shown on x-axis. Significant p-values (p<0.05) between groups are shown above bars for optimal peptides and indicated by *** (p<0.001), ** (p<0.001) and * (p<0.01) for 18mer peptide recognition compared to HLA-B*57/5801 negative individuals(fisher s Exact test). Figure 3. 24

25 Selection of escape mutations within 4 p24 capsid Gag epitopes. A-D Sequence polymorphisms indicated as % sequences of subjects on y-axis with the particular polymorphism shown on the x- axis for ISW9, KF11, TW10 and QW9 p24 epitopes. HLA expression is colour coded as fig 2, B* /B* /B* n=17 (blue), B* /B* /B* n=54 (red), B* /B* /B* n=142 (green) and B* /B* /B* n=989 (white). E IFNγ elispot responses for recognition of QW9 wt and escape peptides, shown as spot forming units/million PBMCs against log peptide titration [μg/ml] in donor N067 (HLA-A*0201/0205, B*5101/5801, Cw*0701/1602) (E). ^ indicates HLA-B*4403 individuals removed from analysis due to selection of B*4403 restricted escape mutations. F Correlation of viral load set-point to the number of p24-gag epitopes with selection of escape mutations. r values represent Spearman Rank values with the corresponding p-values shown below (F). Significant p-values are indicated as ***p<0.0001, **p<0.001, *p<0.01 (Fisher s Exact test) (A-D). Figure 4. Unequivocally defining of novel HLA-B*57/58 restricted CD8+ T cell epitopes. (A) Fine mapping of LW9-Vif epitope using titrated peptide truncations of the predicted epitope in IFNγ elispot using a LW9 specific CTL line, grown out from a chronically infected donor from Zimbabwe, R014 (HLA-A*3001/3301, B*4201/5703, Cw*1701/1801), and used as effector input cells. (B) HLA restriction of LW9 using peptide pulsed or unpulsed partially effecter CTL HLA matched B cell lines only sharing one of the 6 HLA alleles of the R014 CTLs as indicated on the y-axis in an ICS assay. (C) HLA-B*5703 tetramer staining of LW9 Vif specific PBMCs from the same donor (subject R014) as used in A and B. 25

26 Figure 5. Use of HLA-class I tetramers to rapidly define novel HIV-1 CD8+ T cell epitopes. HLA-B*5703 tetramers loaded with the indicated optimal peptide and stained against HLA matched ex vivo donor PBMCs as follows: A, HLA-B*5702 tetramer loaded with QF10 RT (QATWIPEWEF) (subject: N099). B, LF11 p17 (LVWASRELERF) (subject: R014), FF9 RT (FSVPLDEGF) (subject: N087), IAW9 RT (IAMESIVIW) (subject: N102), QF10 RT (QATWIPEWEF) (subject: R014), KF9 Nef (KTAVQMAVF) (subject: N102), HW9 Nef (HTQGFFPDW) (subject: R046, B*5701), QY10 Rev (QAVRIIKILY) (subject: R059), LW9 Vif (LGHGVSIEW) (subject: N102). C, HLA-B*5801 tetramers loaded with: DW10 p24 (DTINEEAAEW) (subject: N067), QW9 p24 (QATQDVKNW) (subject: N067), IAW9 RT (IAMESIVIW) (subject: R007), HW9 Nef (HTQGFFPDW) (subject: N087), KW11 Env (KAYEKEVHNVW) (subject: R076). Numbers in the gate show the percentage of tetramer specific cells gated on live/cd3+/lymphocytes shown as CD8 vs tetramer (B and C) or gated on CD8+ cells for PE and APC tetramer gating (A). Figure 6. Differential selection of HIV viral sequence polymorphisms among HLA-B*5702, B*5703 and B*5801 individuals. Percentage of individuals with sequence variation from wildtype is expressed as % sequence mutation from wildtype (x-axis) calculated from sequences available from n=1202 (Gag), n=426 (Pol), n=443 (Nef) and n=248 (Env/Vif/Rev) individuals and grouped according to HLA-B*57/58 expression color-coded as in figure 2. Significant differences (p <0.05) between each of the three HLA-alleles and HLA-B*57/B*5801 negatives are indicated as ***p<0.0001, **p<0.001, *p<0.01 (Fisher s Exact test). 26

27 Figure 7. HLA-peptide affinity and HLA-peptide stability explain differential targeting of epitopes in HLA-B*5702, B*5703 and B*5801 individuals. ISW9 p24 epitope binding affinity (A) and stability (B) to HLA-B*5702, B*5703 and B*5801 molecules. Immunogenicity (% OLP recognition) (C), binding affinity Kd -1 (nm), classified on a log scale and assessed as previously described (24) (D) and peptide:hla stability (hrs) of peptides measured as recently described (25) (E) to the indicated three colour coded HLA molecules. y-axis show the optimal peptide sequence. Figure 8. HLA:peptide affinity and HLA:peptide stability discriminate between immunogenic and nonimmunogenic optimal peptides and correlate to immunogenicity. HLA:peptide binding affinities (A) and HLA:peptide stability (B) for immunogenic and non-immunogenic peptides. Binding affinity values Kd (nm), classified on a log scale (C), and peptide:hla complex stability (hrs) (D) correlation to the percentage of individuals recognising the corresponding OLP containing the optimal epitope and shown for HLA-B*5702, B*5703 and B*5801 individual groups as pooled data. Numbers in brackets refer to the number of individuals used for percent IFNγ elispot recognition of OLP. Mann Whitney U test was used for comparison of median values of immunogenic vs non-immungenic peptides and r values represent Spearman Rank values with corresponding p-values shown below. p-values <0.05 were considered significant. 27

28 Acknowledgements This work was supported by the Wellcome Trust (PG) and the National Institutes of Health, Grant RO1 AI Contributions of C clade sequence data made by the Seattle CFAR Computational Biology Core are gratefully acknowledged

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32 Leisner, C., N. Loeth, K. Lamberth, S. Justesen, C. Sylvester-Hvid, E. G. Schmidt, M. Claesson, S. Buus, and A. Stryhn One-pot, mix-and-read peptide-mhc tetramers. PLoS One 3:e Leslie, A., D. Kavanagh, I. Honeyborne, K. Pfafferott, C. Edwards, T. Pillay, L. Hilton, C. Thobakgale, D. Ramduth, R. Draenert, S. Le Gall, G. Luzzi, A. Edwards, C. Brander, A. K. Sewell, S. Moore, J. Mullins, C. Moore, S. Mallal, N. Bhardwaj, K. Yusim, R. Phillips, P. Klenerman, B. Korber, P. Kiepiela, B. Walker, and P. Goulder Transmission and accumulation of CTL escape variants drive negative associations between HIV polymorphisms and HLA. J Exp Med 201: Leslie, A., P. C. Matthews, J. Listgarten, J. M. Carlson, C. Kadie, T. Ndung'u, C. Brander, H. Coovadia, B. D. Walker, D. Heckerman, and P. J. Goulder Additive contribution of HLA class I alleles in the immune control of HIV-1 infection. J Virol 84: Leslie, A. J., K. J. Pfafferott, P. Chetty, R. Draenert, M. M. Addo, M. Feeney, Y. Tang, E. C. Holmes, T. Allen, J. G. Prado, M. Altfeld, C. Brander, C. Dixon, D. Ramduth, P. Jeena, S. A. Thomas, A. St John, T. A. Roach, B. Kupfer, G. Luzzi, A. Edwards, G. Taylor, H. Lyall, G. Tudor-Williams, V. Novelli, J. Martinez-Picado, P. Kiepiela, B. D. Walker, and P. J. Goulder HIV evolution: CTL escape mutation and reversion after transmission. Nat Med 10: Macdonald, W. A., A. W. Purcell, N. A. Mifsud, L. K. Ely, D. S. Williams, L. Chang, J. J. Gorman, C. S. Clements, L. Kjer-Nielsen, D. M. Koelle, S. R. Burrows, B. D. Tait, R. Holdsworth, A. G. Brooks, G. O. Lovrecz, L. Lu, J. Rossjohn, and J. McCluskey A naturally selected dimorphism within the HLA-B44 supertype alters class I structure, peptide repertoire, and T cell recognition. J Exp Med 198: Martin, M. P., Y. Qi, X. Gao, E. Yamada, J. N. Martin, F. Pereyra, S. Colombo, E. E. Brown, W. L. Shupert, J. Phair, J. J. Goedert, S. Buchbinder, G. D. Kirk, A. Telenti, M. Connors, S. J. O'Brien, B. D. Walker, P. Parham, S. G. Deeks, D. W. McVicar, and M. Carrington Innate partnership of HLA-B and KIR3DL1 subtypes against HIV-1. Nat Genet 39: Martinez-Picado, J., J. G. Prado, E. E. Fry, K. Pfafferott, A. Leslie, S. Chetty, C. Thobakgale, I. Honeyborne, H. Crawford, P. Matthews, T. Pillay, C. Rousseau, J. I. Mullins, C. Brander, B. D. Walker, D. I. Stuart, P. Kiepiela, and P. Goulder Fitness cost of escape mutations in p24 Gag in association with control of human immunodeficiency virus type 1. J Virol 80: Matthews, P. C., E. Adland, J. Listgarten, A. Leslie, N. Mkhwanazi, J. M. Carlson, M. Harndahl, A. Stryhn, R. P. Payne, A. Ogwu, K. H. Huang, J. Frater, P. Paioni, H. Kloverpris, P. Jooste, D. Goedhals, C. van Vuuren, D. Steyn, L. Riddell, F. Chen, G. Luzzi, T. Balachandran, T. Ndung'u, S. Buus, M. Carrington, R. Shapiro, D. Heckerman, and P. J. Goulder HLA-A*7401-Mediated Control of HIV Viremia Is Independent of Its Linkage Disequilibrium with HLA-B*5703. J Immunol 186: Matthews, P. C., A. Prendergast, A. Leslie, H. Crawford, R. Payne, C. Rousseau, M. Rolland, I. Honeyborne, J. Carlson, C. Kadie, C. Brander, K. Bishop, N. Mlotshwa, J. I. Mullins, H. Coovadia, T. Ndung'u, B. D. Walker, D. Heckerman, and P. J. 32

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34 target functionally important regions of Protease and Integrase in HIV-1 infected subjects. J Transl Med 2: Rousseau, C. M., B. A. Birditt, A. R. McKay, J. N. Stoddard, T. C. Lee, S. McLaughlin, S. W. Moore, N. Shindo, G. H. Learn, B. T. Korber, C. Brander, P. J. Goulder, P. Kiepiela, B. D. Walker, and J. I. Mullins Large-scale amplification, cloning and sequencing of near full-length HIV-1 subtype C genomes. J Virol Methods 136: Sacha, J. B., C. Chung, E. G. Rakasz, S. P. Spencer, A. K. Jonas, A. T. Bean, W. Lee, B. J. Burwitz, J. J. Stephany, J. T. Loffredo, D. B. Allison, S. Adnan, A. Hoji, N. A. Wilson, T. C. Friedrich, J. D. Lifson, O. O. Yang, and D. I. Watkins Gagspecific CD8+ T lymphocytes recognize infected cells before AIDS-virus integration and viral protein expression. J Immunol 178: Sacha, J. B., C. Chung, J. Reed, A. K. Jonas, A. T. Bean, S. P. Spencer, W. Lee, L. Vojnov, R. Rudersdorf, T. C. Friedrich, N. A. Wilson, J. D. Lifson, and D. I. Watkins Pol-specific CD8+ T cells recognize simian immunodeficiency virusinfected cells prior to Nef-mediated major histocompatibility complex class I downregulation. J Virol 81: Schellens, I. M., C. Kesmir, F. Miedema, D. van Baarle, and J. A. Borghans An unanticipated lack of consensus cytotoxic T lymphocyte epitopes in HIV-1 databases: the contribution of prediction programs. AIDS 22: Shehu-Xhilaga, M., S. M. Crowe, and J. Mak Maintenance of the Gag/Gag-Pol ratio is important for human immunodeficiency virus type 1 RNA dimerization and viral infectivity. J Virol 75: Sidney, J., E. Assarsson, C. Moore, S. Ngo, C. Pinilla, A. Sette, and B. Peters Quantitative peptide binding motifs for 19 human and mouse MHC class I molecules derived using positional scanning combinatorial peptide libraries. Immunome Res 4: Tang, J., W. Shao, Y. J. Yoo, I. Brill, J. Mulenga, S. Allen, E. Hunter, and R. A. Kaslow Human leukocyte antigen class I genotypes in relation to heterosexual HIV type 1 transmission within discordant couples. J Immunol 181: Thomas, R., R. Apps, Y. Qi, X. Gao, V. Male, C. O'HUigin, G. O'Connor, D. Ge, J. Fellay, J. N. Martin, J. Margolick, J. J. Goedert, S. Buchbinder, G. D. Kirk, M. P. Martin, A. Telenti, S. G. Deeks, B. D. Walker, D. Goldstein, D. W. McVicar, A. Moffett, and M. Carrington HLA-C cell surface expression and control of HIV/AIDS correlate with a variant upstream of HLA-C. Nat Genet 41: Wearsch, P. A., and P. Cresswell The quality control of MHC class I peptide loading. Curr Opin Cell Biol 20: Yewdell, J., L. C. Anton, I. Bacik, U. Schubert, H. L. Snyder, and J. R. Bennink Generating MHC class I ligands from viral gene products. Immunol Rev 172: Yewdell, J. W., and J. R. Bennink Cut and trim: generating MHC class I peptide ligands. Curr Opin Immunol 13: Yewdell, J. W., and S. M. Haeryfar Understanding presentation of viral antigens to CD8+ T cells in vivo: the key to rational vaccine design. Annu Rev Immunol 23:

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36 Figure 1

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38 Figure 3 A C B D

39 Figure 3 E F Downloaded from on June 30, 2018 by guest

40 Figure 4 A B C B*5703 Tetram mer LGHGVSIEW CD8

41 Figure 5 A B5702 QF10 RT B C B*5702 Tet-APC B* *5703 Tetrame er etramer B*5801 Te B*5702 Tet-PE B5703 LF11 p17 B5703 FF9 RT B5703 IAW9 RT B5703 QF10 RT B5703 KF9 Nef B5703 HW9 Nef B5703 QY10 Rev B5801 DW10 p24 B5801 QW9 p24 CD8 B5801 IAW9 RT CD8 B5703 LW9 Vif B5801 HW9 Nef B5801 KW11 gp120

42 Figure 6 REV ENV/VIF/R NEF POL GAG